In high‑performance motorsport, the pursuit of marginal gains often hinges on the sophisticated interplay between aerodynamics, structural flexibility, and dynamic response under real‑world loads. The Drag Reduction System (DRS) — widely known in the context of formula 1 car racing — offers one of the most effective means to temporarily reduce aerodynamic drag on straights by altering the geometry of the rear wing. By decreasing rear‑wing angle or modifying its configuration, DRS allows the vehicle to decrease aerodynamic drag and increase straight‑line speed, facilitating overtaking manoeuvres while momentarily sacrificing downforce.
Even though the use of DRS may be restricted or phased out under new motorsport regulations, the study remains highly relevant, as it provides insights into the aerodynamic‑structural interactions and drag-reduction strategies that are applicable to a wide range of high-performance vehicle designs.
Within this framework, the recent research led by Professor Alex Zanotti and his team at Department of Aerospace Science and Technology – Politecnico di Milano focuses on the design, analysis, and experimental validation of rear‑wing aerodynamic systems. Their work combines computational fluid dynamics (CFD) simulations with wind‑tunnel testing, allowing the team to explore a range of wing configurations and assess their aerodynamic performance under realistic flow conditions. By systematically investigating both rigid and adjustable mainplanes, the group has generated comprehensive data on drag, downforce, and flow behaviour that guides the design and optimization of high-performance racing wings. This combination of numerical and experimental approaches provides a robust framework for conceptual design, verification, and performance validation of DRS-inspired systems, highlighting how careful integration of aerodynamic design and testing can improve vehicle performance.
Experimental aerodynamic tests were carried out in a wind tunnel using a 1:2-scale model, mounted on a dedicated pylon to ensure correct positioning within the test chamber. A six-axis load cell beneath the pylon measured the variations in aerodynamic loads associated with the DRS configuration.
Data analysis highlighted a strong coupling between aerodynamic loads and the structural dynamic response: activating or deactivating the movable wing generated impulsive excitations that triggered the model’s natural vibration modes, producing transient forces and moments detected by the load cell.
Vicoter s.n.c. (www.vicoter.it) is a highly specialised provider of structural-dynamic testing and analysis services. Its activities span from full-scale GVT and flutter investigations to operational modal analysis, vibration measurements, structural verification under static and fatigue loads. Operating across multiple industrial domains, Vicoter s.n.c. combines experimental expertise with numerical know-how, delivering reliable data and engineering insight to support R&D such as certification processes.
Within a long-term collaboration with the Department of Aerospace Science and Technology – Politecnico di Milano (www.aero.polimi.it), Vicoter contributed to this study by performing bonk tests to identify the vibration modes involved. In addition, Vicoter acquired data during wind-tunnel operations to evaluate Operational Deflection Shapes (ODS) and quantify the aerodynamic damping introduced by the airflow.
In the pre-test phase, the number, location, and reading direction of each measurement point were selected to capture the first bending modes of the pylon along both the X and Y axes, as well as its torsional modes around the Z axis. Axial modes in the Z direction were also investigated, together with all deformable modes of the DRS model. A total of 26 measurement points on the structure and the pylon were identified as necessary to correctly reconstruct the shapes of the first modes, resulting in 55 signals acquired simultaneously.
An impact-based MIMO accelerometer technique was used for the bonk test. The accelerometers were glued onto the structure, while excitation was applied with an instrumented hammer, progressively changing the impact point. Six reference impact points—exciting both the model and the pylon in all three directions—were selected to ensure a high signal-to-noise ratio and to avoid modal nodes. Although the frequency band of interest was limited to 50 Hz, the FRFs were acquired at a high sampling frequency of 2048 Hz using an LMS-Siemens SCADAS316 frontend. Each point was impacted multiple times to reduce measurement noise through averaging.
Numerous wind-tunnel tests were conducted at different airspeeds. The objectives of these tests were twofold: from a static perspective, to measure lift variations caused by the device’s actuation and to verify the actuator’s ability to adjust the DRS configuration under aerodynamic load; from a dynamic perspective, to identify the modes most involved in the transient response, monitor any shifts in natural frequencies or mode shapes due to aeroelastic interaction, and quantify damping at various wind speeds.
The test campaign consisted of seven runs, with wind speed varied from 20 m/s to 50 m/s in 5 m/s increments. During each 85-second test, the DRS was activated and deactivated multiple times, allowing the system to fully decay between successive events. To improve the accuracy of the peak acceleration values, a sampling frequency of 8192 Hz was adopted.
The analysis of colormaps showing the time evolution of the frequency spectra revealed that the most excited modes were those with the highest participation in the wind direction, regardless of whether the system was being activated or deactivated. This behaviour was also confirmed by the OMA (Operational Modal Analysis), which identified only the modes with significant participation along the flow direction. The modal shapes remained consistent across all tests, with cross-MAC values exceeding 0.9. The first bending mode in the front–rear direction was the main contributor to the system’s dynamic response, although other modes participating in the airflow direction also gave a non-negligible contribution.
For Vicoter, the wind-tunnel tests also provided an additional opportunity to assess, in a controlled environment, the capability of the Polymax™ algorithm—used during flight tests for flutter analysis—to identify modes from highly noisy signals.
As wind speed increased, the accelerometer measurements exhibited a progressively higher noise floor. The ratio between the impulsive excitation generated by the DRS actuation and the undisturbed signal gradually decreased, reducing the signal-to-noise ratio and making OMA-based modal identification increasingly difficult.
Despite this, the identification method proved to be very robust: all excited modes were clearly detected with low model complexity, and the resulting shapes were orthogonal and associated with plausible damping values.
Vicoter warmly thanks Alex Zanotti, Luca Riccobene, Donato Grassi, and Thomas Magni for their valuable support, the constructive technical discussions, and the continuous exchange of expertise that significantly contributed to the depth and quality of this work.
